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Lithium iron phosphate intelligent SOC prediction for efficient electric vehicle

Toha, Siti Fauziah and Faeza, Nor Hazima and Mohd Azubair, Nor Aziah and Nizam, Hanis and Hassan, Mohd. Khair and Ibrahim, Babul Salam KSM (2014) Lithium iron phosphate intelligent SOC prediction for efficient electric vehicle. Advanced Materials Research, 875. pp. 1613-1618. ISSN 1022-6680

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Abstract

This paper presents modelling techniques for Lithium Iron Phosphate (LiFePO4) battery in an electric vehicle. Artificial intelligence techniques namely multi-layered perceptron neural network (MLPNN) and Elman recurrent neural network are devised to estimate the energy remained in the battery bank which referred to state of charge (SOC). The New European Driving Cycle (NEDC) test data is used to excite the cells in driving cycle-based conditions under varied temperature range [0-55]0C. Accurate SOC prediction is a key function for satisfactory implementation of Battery Supervisory System (BSS). It is demonstrated that artificial intelligence methods can be effectively used with highly accurate results. The accuracy of the modeling results is demonstrated through validation and correlation tests.

Item Type: Article (Journal)
Additional Information: 4680/35311
Uncontrolled Keywords: Lithium Iron Phosphate, State of charge (SOC), multi-layered perceptron neural network (MLPNN), Elman recurrent neural network and Battery Supervisory System (BSS)
Subjects: T Technology > T Technology (General) > T55.4 Industrial engineering.Management engineering. > T59.5 Automation
Kulliyyahs/Centres/Divisions/Institutes: Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User: Dr. Siti Fauziah Toha
Date Deposited: 06 Feb 2014 16:03
Last Modified: 18 Sep 2017 10:23
URI: http://irep.iium.edu.my/id/eprint/35311

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